Early detection of respiratory disease outbreaks through primary healthcare data

International summary

Abstract

Background: The emergence of coronavirus disease 2019 (COVID-19) highlighted the relevance of surveillance systems in detecting early signs of potential outbreaks, thus enabling public health authorities to act before the pathogen becomes widespread. Syndromic digital surveillance through web applications has played a crucial role in monitoring the spread of SARS-CoV-2. However, this approach requires expensive infrastructure, which is not available in developing countries. Pre-existing sources of information, such as encounters in primary health care (PHC), can provide valuable data for a syndromic surveillance system. Here we evaluated the utility of PHC data to identify early warning signals of the first COVID-19 outbreak in Bahia, Brazil, in 2020. Methods: We compared the weekly counts of PHC encounters due to respiratory complaints and the number of COVID-19 cases in 2020 in Bahia State, Brazil. We used data from December 2016 to December 2019 to predict the expected number of encounters in 2020. We analysed data aggregated by geographic regions and included those where historical PHC data was available for at least 70% of the population. Results: Twenty-one out of 34 regions met the inclusion criteria. Notification of COVID-19 cases was preceded by at least two weeks with an excess of encounters for respiratory complaints in 18 of 21 regions and by four weeks or more in 10 of 21 regions. Conclusions: Digital syndromic surveillance systems based on already established PHC databases may add time to preparedness and response to emerging epidemics.